Commercial Mortgage Default: A Comparison of Logit with Radial Basis Function Networks

The Journal of Real Estate Finance and Economics, 1998

Posted: 9 Jun 1998

See all articles by Athanasios Episcopos

Athanasios Episcopos

Athens University of Economics and Business - Department of Accounting and Finance

Andreas Pericli

ALM & Fixed Income Research

Jianxun Hu

Advanta Mortgage

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Abstract

The use of artificial neural networks in the modeling of foreclosure of commercial mortgages is explored by employing a large set of individual loan histories previously used in the literature of proportional hazard models, and specifically in Vandell et al (JAREUEA: 21(4), 451-480). Radial basis function networks are trained on the same input variables as those used in the logistic model. The networks are shown to be superior to the logistic benchmark in terms of discriminating between "good" and "bad" mortgages. The paper presents a sensitivity analysis on the average loan and offers suggestions for improving defaulting loan prediction.

Note: This is a description of the article and is not the actual abstract.

JEL Classification: R0, G21, G12

Suggested Citation

Episcopos, Athanasios and Pericli, Andreas and Hu, Jianxun, Commercial Mortgage Default: A Comparison of Logit with Radial Basis Function Networks. The Journal of Real Estate Finance and Economics, 1998. Available at SSRN: https://ssrn.com/abstract=97028

Athanasios Episcopos (Contact Author)

Athens University of Economics and Business - Department of Accounting and Finance ( email )

76 Patission Street
GR-104 34 Athens
Greece
+30 21 0820 3364 (Phone)
+30 21 0822 8816 (Fax)

HOME PAGE: http://www.aueb.gr/users/episcopos

Andreas Pericli

ALM & Fixed Income Research ( email )

8200 Jones Branch Drive
Mailstop 375
Mclean, VA 22102
United States
703-903-2429 (Phone)
Not available (Fax)

Jianxun Hu

Advanta Mortgage ( email )

850 Ridgeview Drive
Horsham, PA 19044
215-576-7646 (Phone)
215-444-4697 (Fax)

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